Question Answering
Transformers
PyTorch
TensorFlow
JAX
Rust
Safetensors
English
roberta
Eval Results (legacy)
Instructions to use deepset/roberta-base-squad2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use deepset/roberta-base-squad2 with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "question-answering" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # pip install "transformers<5.0.0" from transformers import pipeline pipe = pipeline("question-answering", model="deepset/roberta-base-squad2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("deepset/roberta-base-squad2") model = AutoModelForQuestionAnswering.from_pretrained("deepset/roberta-base-squad2", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from deepset/roberta-base-squad2: direct link, hf CLI and curl.
- Browser
- Download file 496 MB
-
https://huggingface.co/deepset/roberta-base-squad2/resolve/deedc3e42208524e0df3d9149d1f26aa6934f05f/pytorch_model.bin
- Command line
-
hf download hf://deepset/roberta-base-squad2@deedc3e42208524e0df3d9149d1f26aa6934f05f/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/deepset/roberta-base-squad2/resolve/deedc3e42208524e0df3d9149d1f26aa6934f05f/pytorch_model.bin
496 MB
- Xet hash:
- fc7fd19f6530b09bac74f8d0f1e5262cffc61939421e12361f2a992928c19df4
- Size of remote file:
- 496 MB
- SHA256:
- e0b64ccefc1bcb569b604baea27eb873e5482fdf6eb3ceff1fb5368397db5aed
路
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